Navigation and mapping service providers often use polygons to represent geographic features (e.g., natural features such as lakes, parks, etc.; as well as man-made features such as buildings or other structures) in a geographic database. One common function is finding overlaps between stored polygons and a candidate polygon or candidate point. For example, service providers can use the process of finding overlapping polygons to support many location-based services such as point-of-interest (POI) recommendations, advertising intelligence, database collation or update, etc. However, historical approaches to finding polygon overlaps are often resource intensive and time consuming because they rely on evaluating a large number of stored polygons. Accordingly, service providers face significant technical challenges to enabling an efficient and fast search for overlapping polygons in a geographic database.